Decentralized and distributed continuous replication system for moving devices

ABSTRACT

A replication system for data of mobile devices is disclosed. The data of a mobile device is uploaded to stations in an area. Metadata associated with the objects is stored in a centralized or decentralized system. The metadata can be accessed to identify the stations storing the device&#39;s objects and the data of the mobile device can then be retrieved from the stations and reconstructed.

FIELD OF THE INVENTION

Embodiments of the present invention relate to systems and methods for areplication system for network connectable devices. More particularly,embodiments of the invention relate to a distributed and decentralizedreplication system for IOT (Internet of Things) devices.

BACKGROUND

The IOT is essentially a system of connected devices—devices that areconnected to the Internet. Many of the devices purchased today, fromcars to appliances to speakers, are connected to the Internet and arepart of the IOT. Going forward, it is anticipated that the number ofdevices joining the IOT will increase.

Many of the devices joining the IOT will be mobile IOT devices such ascars and drones. These devices, however, will produce very large amountsof data—more than can be sent to the cloud.

Some of the devices may have some computing power and may be able toperform machine learning based algorithms locally or perform otherprocessing. Other devices, however, will not have this ability eventhough they may be used in scenarios where data collection and retentionis important. For example, drones may have less compute ability thancars. Notwithstanding the differences in computing power, it may beuseful to collect and keep a copy of data generated or gathered by IOTdevices such as cars and drones. This data can be used, for example, foranalysis purposes (e.g., in vehicles including driverless vehicles) orevidence in the case of a crime or disaster. Further, the data stored onthe device may not be available at the time the data is actually needed(e.g., an accident or fire destroys the onboard storage).

As previously stated, connected devices including connected mobiledevices produce huge amounts of data. In fact, the amount of dataprojected to be produced by connected cars is substantially higher thatthe available 5G bandwidth. As a result, it will not be possible tocreate a backup copy of all data generated by connected devices.Further, the storage available on the connected devices themselves islimited and must be deleted as some point. As a result, all of the datacannot be kept for a long period of time and some of the data will beerased.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which at least some aspects of thisdisclosure can be obtained, a more particular description will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only example embodiments of the invention and are not thereforeto be considered to be limiting of its scope, embodiments of theinvention will be described and explained with additional specificityand detail through the use of the accompanying drawings, in which:

FIG. 1 illustrates an example of an area that includes IOT devices andthat includes a replication system for replicating or backing up dataassociated with the IOT devices;

FIG. 2 is a block diagram illustrating an example of data replication inan IOT device;

FIG. 3 illustrates an example of a system and method for reconstructingdata pertaining to an IOT device;

FIG. 4 is a flow diagram illustrating an example of a method forreplicating data; and

FIG. 5 is a flow diagram illustrating an example of a method forreconstructing replicated data.

DETAILED DESCRIPTION OF SOME EXAMPLE EMBODIMENTS

Embodiments of the invention relate to an asynchronous replicationsystem for moving devices (and other devices) including Internet ofThings (IOT) devices. The replication system may be distributed and/ordecentralized. The replication system is configured to stream data tolocal stations or to other connected devices (such as cars or drones)using a fast local link such as, by way of example only, w-gig.Advantageously, this allows the latest data to be on the device itselfand on one or more other locations.

Further, the data or different portions of the data of the IOT devicesmay be streamed to different stations. In one embodiment, the data maybe packaged and transmitted in objects. IOT devices may transmit to aparticular station as long as a connection is sufficient. Because theIOT devices are mobile, they may deliver objects to other stationsovertime. Thus, depending on environmental factors, the objects will bestreamed to available local stations or other devices. A car at astoplight, for example, may stream multiple objects to a nearby stationwhile the same car, after travelling further down the road, may sendanother object to another station.

For example, data associated with a car may include certain data suchcar speed, location, direction over the last time period, engineparameters (RM, heat), onboard computer statuses, sensor data (brakedata, tire pressure data, oil data, etc.), video from the car'scamera(s), audio recordings, and the like or combination thereof. Datafrom a drone may include height data, video data, sound data, deviceparameter data and the like.

For these devices, data is continually being generated. Embodiments ofthe invention replicate this data to stations. Once the data has beenreplicated, the IOT devices can free memory by deleting the replicateddata. The device is not required to delete the data. However, aspreviously stated, because the data stored by the IOT device iscontinually being created and because the onboard memory is limited, itwill be necessary to free memory at some point.

Embodiments of the invention enable the data to be streamed to one ormore stations that may be positioned in the environment. Consequently,the data of a particular IOT device may be distributed across multiplestations. The data may be packaged into an object and provided with orassociated with metadata. The metadata may include device identifierssuch that the data of the device stored on the station can be identifiedfrom other objects stored at the same station.

Although not a requirement, each object may have pointers to thelocations or stations in which previous objects of the same IOT devicereside. Including metadata that allows the objects themselves toreference other objects is not a requirement, however, because metadatathat allows the various objects to be retrieved and reconstructed ispreferably transmitted to the cloud or to decentralized system such as aledger or blockchain. This allows all of the data to be reconstructed asnecessary from the distinct stations. The metadata that allows theobjects to be located may be transmitted directly from the IOT device orforwarded by the receiving station.

The metadata about which station or IOT device contains the actual dataof a particular IOT device can be stored in a centralized location (forexample in the cloud), or in a decentralized list (like a blockchain).This metadata allows the entire data set to be rebuilt by obtaining themetadata and then reading the data from the correct stations.

The actual data included in an object can vary and may be set by defaultor set by a user or the like. For example, for a car, each object maycontain samples from a period of time (e.g., 10 seconds). This mayinclude audio of the last 10 seconds, video and other data as discussedherein.

The data may be replicated by having the IOT device periodicallytransmit data or objects to the closest station or to a station withwhich a connection can be established. In one example, this connectionmay not be a cellular connection, but is another wireless protocol. Thedata or objects may include changes from the last transmission or asample of the changes. The data may also include a sub-set of allpotential data. The object may include only sensor or point-in-timedata.

The IOT device and/or the station may also send metadata describing thelatest changes and/or a station identifier to the cloud or to ablockchain. This information allows the data stored at the variousstations to be reconstructed. For example, in a situation where eachobject contains 10 seconds of video, the entire video stream can becollected from the stations and reconstructed.

FIG. 1 illustrates an example of an environment in which a replicationsystem that is decentralized and distributed may be implemented. FIG. 1illustrates an area 100 that is representative of a geographic area. Thearea 100 is not limited in size. FIG. 1 illustrates an IOT device 104that is mobile and moving in the area 100. The IOT device 104 may be acar, a drone, a plane, a bicycle, a motorcycle, or any other mobiledevice. The IOT device 104 is configured to communicate over a wirelessprotocol. More specifically, the IOT device 104 may include a radiocomponent, a memory, and a processor and is configured to acquire data,process data, package data and transmit data.

The stations 106, 108, 110 and 112 are examples of stations configuredto receive and store data or objects at least from IOT devices. Becausethe stations are not typically mobile, they may be associated with alarger memory than the IOT device 104. In fact, the stations may beconfigured with very large memory in order to receive and store datareceived from multiple IOT devices. Each station may be configured tocommunicate with multiple IOT devices simultaneously. Each station mayalso be connected to the Internet and may include a processor and otherhardware.

The stations may be configured to further transmit data to a repository,such as a data center, for long term storage. This can be accomplishedat non-peak times for example. The stations can be incorporated intoexisting objects. For example, the stations may be incorporated intostoplights, into other signage or in other structures present in thearea 100. The stations can be powered by the grid or using solar powerwhere appropriate. The stations may have a wired and/or wirelessconnection to the Internet that is distinct from the wirelesscommunications established with the IOT devices.

As previously stated, the IOT device 104 may be mobile or is moving inthe area 100. As the IOT device 104 moves in the area 100, the IOTdevice may come into contact with or in the wireless range of aplurality of different stations. The IOT device 104 may establishcontact with different stations at different times. When two or morestations are available, the station with the strongest signal may beselected. When close enough to a particular station to enable wirelesscommunication, one or more objects may be transmitted from the IOTdevice 104 to the station (e.g., the station 108). When the IOT device104 encounters another station such as the station 106, anothersubsequently generated object may be transmitted to the station 106.

For example, the IOT device 104 may be near (e.g., within the wirelessrange of) the station 108 and transmit one or more objects to thestation 108. When the IOT device 104 moves away from (out of wirelessrange) the station 108 and comes close to the station 106, the IOTdevice 104 may transmit different (e.g., newer) objects to the station106. This process can be repeated each time the IOT device 104 is nearone of the stations in the area 100.

As a result, the data of the IOT device 104 is stored in a distributedmanner in a replication system. For example, the IOT device 104 maydeliver an object to the station 108 and then deliver an object to thestation 106. Metadata that identifies the stations storing the objectsof the IOT device 104 and that associates the objects with the IOTdevice 104 may be stored in the cloud or in a decentralized list.Alternatively, or in addition, the object stored at the station 106 mayinclude sufficient information for the object stored on the station 108to be located. This may include a pointer to the station 108 andinformation identifying the object stored at the station 108.

In one example, the metadata delivered to the cloud or stored in thedecentralized list may include a time stamp, the station identifier, ahash of the data (to ensure that the data is not corrupted) and the IOTdevice identifier. With this metadata stored in the cloud or in thedecentralized list, each of the stations 106, 108, 110 and 112 thatstore an object of the IOT device 104 can thus be identifiedindependently of other stations. Further, the objects can be locatedindependently of the order in which the objects were stored. Thestations may be uniquely identified at least with respect to a definedgeographic area.

If an accident occurs to the IOT device 104, certain information may bestored at the IOT device 104. If the data stored on the IOT device 104is not available (damaged, deleted, etc.), then the copies of the datadelivered to one or more of the stations can be accessed. In an accidentor for other reasons, objects from all associated IOT devices can beevaluated.

As previously stated, the data stored locally on the stations can beaccessed using a centralized system and/or a decentralized system. Inone example, the IOT device 104 (or the stations receiving the objects)may send metadata to the cloud 102. The metadata sent to the cloudidentifies the station that store the objects of the IOT device 104.Alternatively, a blockchain could be used to store information thatidentifies which stations store the objects of the IOT device 104.

Because the amount of data received by the stations is large, theobjects delivered to the stations may also be subject to a retentionpolicy. The objects may be erased after a certain time period ortransmitted to a less expensive low tier storage.

A retention policy will allow the data to be erased after a period oftime and the policy can be set when the objects are being created, andcan be modified by using the central cloud or the block chain list.

One advantage of using a blockchain is that a completely decentralizedreplication system is obtained. If metadata is relatively small is size,sending the metadata to cloud should not be problematic (for exampleevery minute send metadata on the location of the last objects). Thisschedule can be adjusted based on when an object is sent. For example,metadata may be sent every time an object is sent or when an object issent to a different station.

FIG. 2 illustrates an example of a replication system. The replicationsystem shown in FIG. 2 illustrates an IOT device 210 at two points intime (IOT 210 a at time x) and (IOT 210 b at time y). At time x, the IOT210 a is near or able to communicate with a station 202. The object 212is thus transmitted to and stored by the station 202. The object 212 isstored along with other objects stored by the station 202.

At time y, the IOT 210 b is near or within range of the station 206. TheIOT 210 b transmits an object 214 to the station 206, which is stored inthe objects 208. At time y (a similar process occurs at other times withother stations).

In this example, metadata 216 is also generated and stored in acentralized system or a decentralized system. The metadata 216 may begenerated by the IOT device 210 or by the stations and may betransmitted by the IOT device or by the stations to the replicationsystem. The metadata 216 may identify or associate the station 202, theobject 212, a timestamp, the IOT device 216 or the like. The metadata216 thus allows all stations storing objects associated with the IOTdevice 210 to be located and accessed. Alternatively, the object 214,stored in the objects 208, points to the object 212, stored in theobjects 204. This allows the objects to be identified in another mannerif the centralized/decentralized system is not available.

FIG. 2 illustrates that the stations 202 through 206 may store a seriesof linked objects. The metadata 216 can be used to retrieve the objectsand reconstruct or evaluate the associated objects or data. Theblockchain or cloud data may also allow objects to be recovered even ifthe data or an object is no longer available at a particular stationdue, for example, to a retention policy. Thus, if a series of objectsincludes three objects, it may be possible to retrieve one or more ofthese objects in any order as long as they are still stored at thestations.

Regardless of where the metadata 216 is stored, the entire data set orportions thereof can be obtained and rebuilt by obtaining the metadataand then reading the data from the appropriate locations.

FIG. 3 illustrates an example of a system for reconstructing IOT devicedata. In this example, the replication system 300 may be a cloud basedapplication or decentralized application. Thus, the replication system300 may store metadata in a centralized manner such as the cloud 318 orin a decentralized manner such as in a blockchain 310.

When access to the objects generated by or associated with an IOT deviceis needed, the appropriate metadata can be identified using a deviceidentifier (e.g., a serial number, a registration number, or otheridentifier. In other words, access to a cloud relational database can bebased on the device identifier and the blockchain can be similarlyaccessed.

Once access to the metadata is achieved, the replication system 300 willidentify the appropriate stations or stations that store the IOTdevice's objects and then access those appropriate stations to retrievethe relevant objects. In this example, the replication system 300 mayaccess the station 302, the station 304, and the station 306 toretrieve, respectively, the object 312, the object 314, and the object316. These objects can then be processed and output as reconstructed IOTdata 320. This may be presented in a display in text form. Some of thedata may be converted to graphic form. For example, engine temperature,speed, direction and other parameters can be displayed graphically orthe like.

The IOT data 320 can be reconstructed from whatever data is present orstill stored at the stations 302, 304 and 306. For example, the object314 may not be present on the station 304. In this case, thereconstructed IOT data 320 will include only the data from the object312 and the object 316.

In another example, the hash included in the metadata may be used toensure that the object or data retrieved from the stations is notcorrupt or has not been changed.

FIG. 4 illustrates an example of a method for replicating dataassociated with an IOT device that is mobile. The method 400 may beginwhen an IOT device detects a station 402. Once a station is detected anda connection is established, the IOT device may prepare an object 404and upload the object 406 to the station.

The IOT device may prepare multiple objects for transmission andtransmit the objects. If an object is not fully transmitted before theconnection is terminated or insufficient, the object is retransmitted tothe next station encountered by the IOT device. The objects can betransmitted in any order and do not need to be transmitted in the orderin which they are created. The associated metadata, such as thetimestamp, allows the objects to be rebuilt in order. In anotherexample, the object may be transmitted to another IOT device that mayhave more storage if necessary. For example, a company may have multiplemobile IOT devices that are able to share data as discussed herein.Typically, the IOT device's data is transmitted to a station directly orforwarded to a station by another IOT device.

This process occurs and the IOT device moves into and out of the rangesof the various stations located in an area. Whenever an IOT device is inrange of a station, objects can be transmitted to that object.

At 408, metadata is transmitted to the replication system and stored ina cloud based database, in a decentralized ledger or blockchain, or inanother suitable manner. This metadata is transmitted when possible oris forwarded by the stations.

FIG. 5 illustrates an example of a method for rebuilding the data of anIOT device from a replicated system. Initially, a request is receivedfor the metadata 502. The request typically identifies the IOT device sothat the relevant metadata can be identified and returned in response tothe request. Once the metadata is retrieved 504, the stations identifiedin the metadata are accessed 504 to obtain the relevant objects. Theseobjects are then reconstructed 506 into the IOT device's data.Reconstructing the data may include ensuring that the retrieved data hasnot been corrupted or changed, based for example on a hash included inthe metadata.

Thus, the latest data associated with an IOT device may be available atthe device itself

It should be appreciated that the present invention can be implementedin numerous ways, including as a process, an apparatus, a system, adevice, a method, or a computer readable medium such as a computerreadable storage medium or a computer network wherein computer programinstructions are sent over optical or electronic communication links.Applications may take the form of software executing on a generalpurpose computer or be hardwired or hard coded in hardware. In thisspecification, these implementations, or any other form that theinvention may take, may be referred to as techniques. In general, theorder of the steps of disclosed processes may be altered within thescope of the invention.

The embodiments disclosed herein may include the use of a specialpurpose or general-purpose computer including various computer hardwareor software modules, as discussed in greater detail below. A computermay include a processor and computer storage media carrying instructionsthat, when executed by the processor and/or caused to be executed by theprocessor, perform any one or more of the methods disclosed herein.

As indicated above, embodiments within the scope of the presentinvention also include computer storage media, which are physical mediafor carrying or having computer-executable instructions or datastructures stored thereon. Such computer storage media can be anyavailable physical media that can be accessed by a general purpose orspecial purpose computer.

By way of example, and not limitation, such computer storage media cancomprise hardware such as solid state disk (SSD), RAM, ROM, EEPROM,CD-ROM, flash memory, phase-change memory (“PCM”), or other optical diskstorage, magnetic disk storage or other magnetic storage devices, or anyother hardware storage devices which can be used to store program codein the form of computer-executable instructions or data structures,which can be accessed and executed by a general-purpose orspecial-purpose computer system to implement the disclosed functionalityof the invention. Combinations of the above should also be includedwithin the scope of computer storage media. Such media are also examplesof non-transitory storage media, and non-transitory storage media alsoembraces cloud-based storage systems and structures, although the scopeof the invention is not limited to these examples of non-transitorystorage media.

Computer-executable instructions comprise, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. Although the subject matter has been described inlanguage specific to structural features and/or methodological acts, itis to be understood that the subject matter defined in the appendedclaims is not necessarily limited to the specific features or actsdescribed above. Rather, the specific features and acts disclosed hereinare disclosed as example forms of implementing the claims.

As used herein, the term ‘module’ or ‘component’ can refer to softwareobjects or routines that execute on the computing system. The differentcomponents, modules, engines, and services described herein may beimplemented as objects or processes that execute on the computingsystem, for example, as separate threads. While the system and methodsdescribed herein can be implemented in software, implementations inhardware or a combination of software and hardware are also possible andcontemplated. In the present disclosure, a ‘computing entity’ may be anycomputing system as previously defined herein, or any module orcombination of modules running on a computing system.

In at least some instances, a hardware processor is provided that isoperable to carry out executable instructions for performing a method orprocess, such as the methods and processes disclosed herein. Thehardware processor may or may not comprise an element of other hardware,such as the computing devices and systems disclosed herein.

In terms of computing environments, embodiments of the invention can beperformed in client-server environments, whether network or localenvironments, or in any other suitable environment. Suitable operatingenvironments for at least some embodiments of the invention includecloud computing environments where one or more of a client, server, ortarget virtual machine may reside and operate in a cloud environment.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. The scope of the invention is, therefore, indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

1. A method for reconstructing data of a mobile device, the methodcomprising: receiving a request for the data of the mobile device,wherein data objects constituting the data are stored in a distributedmanner at different locations in an environment, wherein each of thedata objects is associated with a pointer; retrieving a first dataobject from a first station; accessing the first data object to obtain afirst pointer, wherein the first pointer identifies a location of a nextdata object stored at a next station; retrieving the next data objectfrom the next station using the pointer included in the first dataobject; retrieving other data objects from other stations using thepointers icluded in the data objects; and reconstructing the data fromthe retrieved data objects.
 2. The method of claim 1, further comprisingstoring the data in a distributed manner such that each of the dataobjects are stored at different locations in an environment.
 3. Themethod of claim 1, further comprising identifying the first locationusing the request.
 4. The method of claim 3, wherein the first stationand the next station are solar powered and/or incorporated into objectsin the environment.
 5. The method of claim 1, wherein the first stationstores more than one of the data objects of the data, wherein the dataobjects stored at the first station are separated in time.
 6. The methodof claim 1, wherein the request is filled using metadata stored in ablockchain.
 7. The method of claim 1, further comprising verifying thatthe retrieved data objects have not been changed or corrupted beforereconstructing the data from the retrieved data objects.
 8. The methodof claim 7, further comprising reconstructing the data using theretrieved data objects include less than all of the data objectsassociated with the data.
 9. The method of claim 1, further comprisingreceiving the request at a replication system, the request including amobile device identifier and accessing metadata to identify the firststation or receiving the request at the first station.
 10. The method ofclaim 9, wherein the metadata includes a time stamp, a stationidentifier, and a hash of the data object.
 11. A non-transitory computerreadable medium comprising instructions for executing a method forbacking up a database with a backup server and an agent operating on aclient machine, the method comprising: receiving a request for the dataof the mobile device, wherein data objects constituting the data arestored in a distributed manner at different locations in an environment,wherein each of the data objects is associated with a pointer;retrieving a first data object from a first station; accessing the firstdata object to obtain a first pointer, wherein the first pointeridentifies a location of a next data object stored at a next station;retrieving the next data object from the next station using the pointerincluded in the first data object; retrieving other data objects fromother stations using the pointers included in the data objects; andreconstructing the data from the retrieved data objects.
 12. Thenon-transitory computer readable medium of claim 11, further comprisingstoring the data in a distributed manner such that each of the dataobjects are stored at different locations in an environment.
 13. Thenon-transitory computer readable medium of claim 11, further comprisingidentifying the first location using the request.
 14. The non-transitorycomputer readable medium of claim 13, wherein the first station and thenext station are solar powered and/or incorporated into objects in theenvironment.
 15. The non-transitory computer readable medium of claim11, wherein the first station stores more than one of the data objectsof the data, wherein the data objects stored at the first station areseparated in time.
 16. The non-transitory computer readable medium ofclaim 11, wherein the request is filled using metadata stored in ablockchain.
 17. The non-transitory computer readable medium of claim 11,further comprising verifying that the retrieved data objects have notbeen changed or corrupted before reconstructing the data from theretrieved data objects.
 18. The non-transitory computer readable mediumof claim 17, further comprising reconstructing the data using theretrieved data objects include less than all of the data objectsassociated with the data.
 19. The non-transitory computer readablemedium of claim 11, further comprising receiving the request at areplication system, the request including a mobile device identifier andaccessing metadata to identify the first station or receiving therequest at the first station.
 20. The non-transitory computer readablemedium of claim 19, wherein the metadata includes a time stamp, astation identifier, and a hash of the data object.